Build In-Demand Data Science and AI Skills

The AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact is ideal for: 

• Early-career professionals or senior managers (IT Managers, Business Intelligence Analysts, Data Science Managers, Management Consultants, and Business Managers) who want to apply AI, Data Science, and Machine Learning techniques in their firms. 

• Data Scientists, Data Analysts, or Business Analysts who wish to turn vast volumes of data into valuable insights 

• Entrepreneurs interested in innovation with the assistance of AI, Data Science, and Machine Learning techniques 

• Those with academic or professional training in Applied Statistics or Mathematics will find the program easier to learn. However, participants without such a background can also complete the program, provided they are ready to put in extra effort. Great Learning will offer the required assistance.

The application process is conducted on a rolling basis and will close once the required number of candidates are enrolled. Apply early to secure your seat. To ensure your chances of securing a seat, we encourage you to apply as early as possible.

A successful AI and Data Professional needs a firm grasp of coding skills. Here are the key skills that help a professional learn Data Science: 

• Python: Python is the most widely used language in the field of data analysis and Machine Learning. 

• Foundational Knowledge of Other Languages: Familiarity with R, SQL, and SAS is essential, especially for statistical analysis and database management. Some roles may also require exposure to Java, Scala, or Julia. 

• Understanding of the Data Workflow: Beyond programming, you’ll need to know how to work with tools for data acquisition, cleaning, transformation, warehousing, and visualization.

The registration process for this AI and Data Science program is as follows: 

• Step-1: Application Form Register by completing the online application form. 
• Step-2: Fill Application Screening A panel from Great Learning will assess your application based on academics, work experience, and motivation. 
• Step-3: Join Program After a final review, you will receive an offer for a seat in the upcoming cohort of the program.

The total program fee is USD 2500.

No. All required learning materials are provided online through the Learning Management System (LMS). Because these fields continue to evolve, you will also receive a list of recommended books and resources for optional, in-depth exploration.

Applicants can pay the program fee through Bank Transfer and Credit/Debit Cards. They can also pay in easy installments using PayPal credit options and get interest-free payments for up to 6 months (Note that these services are subject to credit approval by PayPal). [For further details, please get in touch with us at dsml.mit@mygreatlearning.com]

Please note that submitting the registration fee constitutes enrollment in the program, and the cancellation penalties outlined below will be applied. If you are unable to attend your program, please review our dropout and refund policies below: 

• Dropout requests received within 7 days of enrollment and more than 42 days prior to the commencement of the program will incur no fee. Any payment received will be refunded in full. 

• Dropout requests received more than 42 days prior to the program but more than 7 days after the acceptance are subject to a cancellation fee of USD 250. 

• Dropout requests received 22-41 days prior to the commencement of the program are subject to a cancellation fee equal to 50% of the program fee. 

• Any dropout requests received fewer than 22 days prior to the commencement of the program are subject to a cancellation fee equal to 100% of the program fee. 

• No refund will be made to those who do not engage in the program or leave before completing a program for which they have registered.

We accept corporate sponsorships and can assist you with the process. [For more information, please write to us at  [dsml.mit@mygreatlearning.com]

Yes, there is an increasing demand for AI, Data Science, and Machine Learning professionals across a wide range of industries, including Technology, Healthcare, Cybersecurity, Finance, Oil & Gas, Transportation, Education, Talent Acquisition, Inventory Management, E-commerce, and more. 

As organizations increasingly adopt AI and data-driven decision-making, professionals skilled in AI, Data Science, Machine Learning, and Generative AI are in high demand. These skills offer strong opportunities for career growth, leadership roles, and long-term industry relevance. 

Employment of data scientists is projected to grow 34 percent from 2024 to 2034, significantly faster than the average growth rate for all occupations. If you’re looking to build a future-proof career, now is the time to upskill in AI, Data Science, and Machine Learning.

To become a Data Scientist, you need to have a blend of technical expertise, analytical thinking, and real-world problem-solving skills. If you have a strong academic background, that will help you learn the concepts related to the field. 

Here’s how you can start: 

• Build a strong foundation in mathematics, statistics, and programming. 
• Gain hands-on experience with tools used in the industry. 
• Develop applied knowledge through projects that simulate real-world data challenges. 
• Strengthen your understanding of Generative AI, AI, and Machine Learning techniques.

• Growing demand in Business: Companies are leveraging AI and Data Science to reduce costs, improve marketing effectiveness, launch better products, and tap into new markets. 

• Data-driven strategy making: Gartner has forecasted that many corporate strategies will highlight data and analytics as essential business competencies. 

• Expanding applications: From healthcare and finance to retail and tech, Data Science is shaping decision-making and driving innovation across industries. 

• Career longevity: With data at the core of digital transformation, professionals with expertise in AI, ML, and Data Science are well-positioned for long-term career growth. 

As industries increasingly rely on data to drive innovation and growth, the need for skilled Data Science professionals will only continue to rise. 

Gaining expertise in Artificial Intelligence, Machine Learning, and Data Science is a smart investment for you to future-proof your career.

Machine Learning refers to a group of techniques used by data scientists that allow computers to learn from data. From leisure to work, our lives are made easier with Machine Learning. The responsibilities of a Machine Learning specialist encompass a spectrum that extends from creating Machine Learning models to retraining systems.

Data Science is a field of study that uses a scientific approach to extract meaningful insights from data. Meaningful insights are derived from data sets, generating knowledge that advises recommendations for business growth.

Organizations across industries increasingly rely on advanced Data Science and Machine Learning to drive strategic decision-making and improve business outcomes. Here’s how Data Science and Machine Learning create impact. 

Inform stronger business strategies. 

Leading companies use data-driven insights and machine learning models to design effective business plans, optimize operations, and accelerate growth. 

Deliver solutions that meet customer needs. 

Organizations with clear data strategies can anticipate market trends, innovate faster, and build products that offer greater value to end users. 

Reduce operational costs.

For small and medium-sized enterprises, AI, Data Science, and Machine Learning enable more efficient processes and cost-effective solutions, helping them stay competitive despite limited resources. 

This combination of strategic insight, customer-centric innovation, and operational efficiency is why Data Science and Machine Learning have become essential capabilities for modern businesses.

The average salary of an AI professional is $184,757. For a Data Scientist, it is $129,294 and for a Machine Learning Specialist, it is $186,067.